Global and local gravity field recovery from satellite-to-satellite tracking
Bibliographic record
Abstract
The main objective of this thesis is the gravity field recovery using satellite-to-satellite tracking methods. Based on new technologies like the global positioning system and accelerometers satellite-to-satellite tracking yields a dramatic improvement in the de- termination of the Earth gravity field. Two dedicated satellite missions, namely the CHAllenging Minisatellite Payload (CHAMP) and the Gravity Recovery And Climate Experiment (GRACE) are underway. This work describes the processing of the satel- lite data from CHAMP and GRACE based on the energy balance approach. The first part discusses the global gravity field recovery from CHAMP. Specifically, it aims at a reprocessing of kinematic position data and at a refinement of the data processing strategies. Although the energy balance approach is theoretically simple, its imple- mentation proved to be quite challenging. By refining the processing techniques an improvement of up to 30\% is reached for the low degree spherical harmonic coefficients. Nevertheless, the solutions still depend strongly on the variability of the groundtrack. The quality of the monthly solutions can vary up to one order of magnitude. To ad- dress this challenge, an in-depth analysis gives new insight into the phenomenon, and a new and unique combination method with GRACE data is presented, which yields a more homogeneous set of solutions and reaches the edge of the recoverability of a time-variable gravity signal from high-low satellite-to-satellite tracking missions. In the second part the energy balance approach is applied to the GRACE mission. Pre- vious attempts of expressing the kinetic energy in terms of the K-band measurement make use of an approximation. In this work, an exact representation is introduced and is validated by simulations. In the third part, the aim is to make optimal usage of the data distribution in the high latitude area. For this, interpolation and downward continuation techniques are investigated and an improvement, compared to the global solutions, is achieved. Overall, the analysis provides new and valuable insight into the data processing of satellite-to-satellite tracking data using the energy balance approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".